November 2011

November 29, 2011

During an earlier phase of our research, we identified the prospective information needs of our various stakeholders: elders, caregivers, occupational therapists and primary care physicians. In particular, our elders were quite interested in real-time or daily information about their performance of their everyday activities, but didn’t find a lot of value in long-term data or trends. They weren’t opposed to the long-term data, but they really wanted to have the daily information in order to see if they had taken their medication, and to see how well they were doing each day.

We designed the visualization below to run as an application on a Samsung Galaxy 10.1” tablet. The visualization has three horizontal panels, one for each of the ODLs that our sensing systems are tracking: medication taking, making phone calls and coffee-making. The large type size, the colors used and the simple design were purposefully chosen to make it easy for the elders to consume the information.

For medication tracking, we present information about morning and evening pills. In the visualization below, you can see that the subject took their morning medicine on time at 5:07 a.m., but had difficulty determining the right day of the week, having opened the Sunday and Monday doors before correctly opening the Tuesday door. The subject missed the evening pill completely. The two bar charts on the right indicate how timely the subject was in taking his or her medicine and how well the subject performed the task. Because the subject missed his or her evening medicine, the timeliness bar chart is red . The other chart is yellow to indicate his or her difficulty in selecting the correct pillbox door. These bar charts are intended to serve as quick additional abstractions to make it easy to consume the medicine-taking information.

For the phone calls, the visualization indicates the number of calls made and, of those, the number of times the user . The bar chart provides a summary of how well the user performed this task.

For coffee-making, the visualization indicates whether the subject made coffee correctly. In particular, it shows whether the subject performed each of four key coffee-making tasks correctly: getting water, adding the coffee, placing the carafe in the coffee maker and starting the machine. In this case, the subject performed all four tasks correctly, which is what the associated bar chart indicates.

We are still going to provide a long-term visualization to some of our subjects to see what value it can provide, despite their seeming lack of interest. This will be a more traditional line graph, with time on the horizontal axis, and the quality of the performance of the task on the vertical axis. Subjects will be able to click on any of the data points to receive the regular daily view for the chosen day. We expect that by providing both kinds of views, we can improve subjects’ awareness of their own performance, and that this will cause them to engage others in discussions (e.g., caregivers, occupational therapists, doctors) about their abilities, with the goal of improving their performance over time.

November 24, 2011

One idea that pervades each of the Project HealthDesign studies is that computing and advanced technology has the potential to change both people’s impressions of their health and their actual health. At least that’s the promise. One of the challenges is that these positive changes often occur over a long period of time, and usually require individuals to integrate a new technology into their lives.

In human-computer interaction, the research field I call home, most of the studies of technologies for behavior change occur over a few weeks, with only a few lasting more than a month. The difficulties in running a longer study are well-documented: recruitment, attrition of participants, maintaining ecological validity while keeping the study as “clean” as possible, researcher fatigue, analysis strategies, funding, etc. Additionally, researchers are able to conduct research and get papers published without conducting such long studies.

The benefits too are well-documented: a long-term study may be the only reasonable and ecologically valid way to study the impact of a technological intervention, novelty effects of introduced technologies are minimized, there’s more time to test out technology in the field and to evolve it before needing to collect data, it gives time for users to feel comfortable with researchers and introduced technologies, and it provides an opportunity to study phenomena that occur over a long period of time.

In our project, we have the opportunity to conduct a long-term study with a few of the early-stage users of our technology. We reported on their use of visualizations of their activities after they had used our embedded assessment system for four months. Our subjects have now used our system for about a year, and we are planning on a follow-up study to understand 1) whether the problems they noticed in the performance of everyday activities caused them to change their behavior to improve performance, 2) whether repeated but infrequent reflection on their data helps them understand their performance data better than with a one-time reflection, and 3) whether our users still find value in the embedded assessment system now.

Although short-term studies of such technologies are useful and common, truly understanding how performance of activities changes over time requires a long-term study.

November 22, 2011

It’s a little too early to take a victory lap, but the stars seem to be aligning for a significantly changed health care system – one that actively engages patients as partners in achieving health and wellness – within the next few years. What are the reasons for our optimism?

On November 2, the Centers for Medicare and Medicaid Services (CMS) released the final rule governing Accountable Care Organizations (ACOs) established under the new Medicare Shared Savings Program. Under this rule, providers in ACOs who can deliver care to Medicare beneficiaries at costs below what Medicare typically pays will be able to share a fairly significant portion of the savings. More than half of Medicare beneficiaries are treated for five or more chronic conditions a year. As a result, achieving savings for this population will depend in part on how well they are actively engaged in managing their health and wellness, such as through the use of personal health records (PHRs) and other technologies that assist patients in self care and in engaging with their clinical care teams more regularly. The Project HealthDesign grantee teams are already providing examples of how such technology can be leveraged to make a difference in individual and population health outcomes.

The Health IT Policy Committee has recommended that Stage 2 of meaningful use require health care professionals and hospitals to provide patients the capability to electronically view — and securely download on demand — relevant portions of their health information. This could significantly increase the demand for PHRs, applications or devices that help individuals securely store, share and make use of their personal health information. Although the official criteria for Stage 2 have not yet been set, the Obama Administration has already implemented this “Blue Button” capability for My HealtheVet and MyMedicare.gov. I am also hearing that vendors of certified electronic health record products are already building this capability into product updates.

The Office of the National Coordinator for Health IT (ONC) rolled out its consumer engagement and education initiative in September. As part of that initiative, health care organizations are encouraged to “take the pledge” to provide patients with “secure, timely, and electronic access to their health information” and to encourage them to use the information to improve their health and their care. In the legislation that created the CMS EHR Meaningful Use Incentive Program, Congress also included a provision that amended HIPAA to require health care entities to provide patients with electronic copies of their health data if that data is stored electronically; entities are also required to send a patient’s copy to another provider or the patient’s PHR upon request. We expect the regulations to implement this provision to be finalized early next year.

Early in 2012 we will know more about whether these optimistic predictions will bear fruit, so stay tuned.

November 18, 2011

I am visiting Southern India for six months — I came in June and will leave in late December. In keeping with my work on dwellSense, I have been looking for opportunities in India where advanced technologies, or at least better information, can be used to enhance clinical practice and personal decision-making. Very unscientifically, I have observed a few things that suggest that India is in need of such technology.

One observation is the huge number of advertisements for help for people with diabetes. Apparently, adult-onset diabetes has become a common issue as India’s growing middle class takes on more of a Western lifestyle and diet. As my cardiologist constantly tells me, “Indian bodies were not made to handle Western diets.”

Another issue is the huge number of people living below the poverty line. I don’t have exact numbers, but it is close to half a billion people, even with the poverty line set quite low (daily per person: 31 Indian Rupees in urban areas, which equates to $0.62 U.S. Dollars, and 25 Rupees in rural areas à $0.50 U.S. Dollars). Many of those individuals can’t afford medical care nor can they take the time to manage their health issues unless an acute problem develops. Therefore, the ability to collect observations of daily living (ODLs) in an unobtrusive, low-cost manner seems crucial.

A third observation is that although all doctors rely on self-reports from patients, homeopathic and ayurvedic doctors here seem to only rely on these reports and what they can observe during a visit. There are rarely, if any, tests that are conducted to confirm or substantiate the patient self-reports. This calls for the collection of data that would help the diagnostic process.

The main issues here are time, cost and literacy. Thinking around how to make technologies that require little manual effort, are cheap and don’t require a literate population or training, is what’s needed. These requirements might also apply to a number of other problems on the subcontinent, but they certainly apply here as well.

November 16, 2011

As director of Project HealthDesign, a national program of the Robert Wood Johnson Foundation that aims to explore how personal health records (PHRs) and patient-sourced data might improve health and health care, I applaud this proposed rule. Allowing patients direct access to lab test reports is an appropriate and much-needed step toward equipping them to access, understand and act on their own health data. My work with Project HealthDesign has shown me that individuals are ready for an era of data-driven health care. Patients are hungry not only for access to lab test reports and clinical visit data, but also for access to more and different kinds of health data to use in conversations with their clinicians. We’re excited to see how patients, when equipped with their own health data, might share richer insights about their everyday health with clinicians and take charge of their health between clinical visits. That’s why we see this proposed rule as a big step for patients.

However, I also recognize that changing the flow of information is going to change the clinical conversation. Everyone needs to be involved in order to ensure that this process remains efficient and effective. That’s why I urge you to concurrently develop patient education tools that will allow patients to understand and minimally interpret lab test report data. At the same time, we must also work to prepare clinicians to participate in this new era of data-driven health care.

This comment was submitted to HHS in response to a proposed rule that would allow patients direct access to their lab test reports. To read the proposed rule, visit regulations.gov.

November 14, 2011

Anyone doing research about records of any kind knows the challenges of handling missing data. We often hear about epidemiologists who struggle to find patterns in incomplete data sets, clinicians who carefully interview patients and family members to fill in the gaps in a medical record, and so on. This problem becomes particularly acute, however, when you are monitoring the data in real time. In some cases, missing data can mean we need to act in some way, but in other cases, it’s nothing to worry about. Two examples tell this story pretty well: developmental activities and appointments.

The Estrellita application asks parents to track the activities they do to bond with their babies, help them develop, and so on. When parents report doing these activities, we give them encouraging messages like “Great job!” and “Your baby loves it when you sing to him.” They also earn badges on their phones for each activity. In this case, because recording the data is actually part of an intervention to encourage these activities, lack of data requires additional intervention. So, if we get no data for a couple of days, then the application reminds parents to do some of the activities and to record them.

On the other hand, sometimes a lack of data doesn’t indicate a problem at all. The Estrellita application asks parents about their experiences with each clinical appointment a few hours after scheduled appointment times. If they don’t answer in that window, we dismiss the question, because self-report gets more unreliable the longer we wait. One of the mothers in our study wanted to be able to keep all her appointment information together, so she entered old appointments from before the study started. Because the appointments were so long ago, they didn’t trigger the additional questions about how they went. So, when one of our case managers logged in to check on this parent, it looked like she had missed a lot of appointments. The case manager was moments away from intervening when she realized that these appointments all predated the study enrollment date. If that baby had really missed that many appointments, there could have been something wrong. In this case, however, the missing data were misleading. Luckily, we were able to make a fix for this situation quickly, and in the case of appointment data, we now have three categories: attended, did not attend, and no information.

Getting complete medical records in a setting in which people are trained to create and manage them (like hospitals) is difficult and complex. Doing the same in homes, schools, and other non-clinical settings can be downright impossible. Through our work, we hope to learn a little more about what to do when we have imperfect or missing data, and we are interested to see how the other projects handle this challenge as well.

November 10, 2011

Katherine Kim, M.P.H., MBA, iN Touch Principal Investigator, San Francisco State University

A meta-review by Webb, et al.² showed that Internet and mobile health interventions designed based on a behavioral theory resulted in better health outcomes with larger effect sizes than those that were not based on a theory. Of the studies included in the review, those that had used Aizen’s Theory of Planned Behavior were the most successful in improving health outcomes. Aizen’s Theory states that individual attitudes and social norms contribute to motivation. But, motivation alone is not sufficient to yield behavior change. There must also be an adequate level of perceived behavioral control which means the individual must think they possess the ability to make the change (and have the capability to make the change). Sounds good, but how do you actually design based on a theory?

For iN Touch, here’s how we thought about it:

For motivation, we needed to elicit individual attitudes/beliefs/values and reinforce positive social norms. The health coach drew out the participant’s individual attitudes through conversation and reinforced the values of health, well-being, and empowerment to make change. She also facilitated self-reflection about the ODLs and identification of trends and patterns in the combinations of ODLs. Weigh-ins and measurements were also a form of reinforcement by revealing objectively whether behavior changes each person made were effective or not. These contributed to motivation in an ongoing way.

We spent a great deal of effort designing perceived behavioral control, using both online and offline tools. The iN Touch application itself was a tool for behavioral control because it allowed the participant to capture the ODLs, review them in real-time, and conduct ad hoc comparisons. We designed the application within a "Five Clicks, Five Minutes" (per day) rule our Youth Advisory Board provided to minimize data entry burden (Sabee, et al.¹). Our post last month provided a detailed overview of the application. The iPod Touch device itself is portable and highly accessible, further contributing to perceived behavioral control.

Offline, we provided participants with a “My Experiment” tool for weekly goal setting and action planning. The key to this coaching tool is it provides the participant a way to make a short-term commitment, prepare for any obstacles, assess their level of confidence, and plan for follow-up. It gives them permission to try out a behavior change and have full control over the conduct of their experiment.

Finally, our intervention included multi-modal interaction with the health coach in order to provide support when and where the participant needed it, another way of putting control in the participant’s hands. Participants were able to meet with the health coach in person or by phone, during scheduled or drop-in appointments, and communicate via text message. All of these strategies contributed to perceived control by participants.

We used the theory of planned behavior to inform both design of the technology and programmatic elements. The use of health behavior change theory in technological design is still emerging. We are eager to hear about other examples where this has been applied. Please share your experiences with us in the comments.

References:

¹ Sabee CM, Kim KK, Charles J, Logan H, Young E. (October, 2011). Five Clicks, Five Minutes: Providing a Voice for Youth with Obesity and Depression with a Mobile Health Platform. Manuscript presented at the International Conference on Communication in Healthcare: Chicago, IL.

November 09, 2011

The American Medical Informatics Association (AMIA) recently held its fall symposium in Washington, D.C. This was the fifth symposium I’ve attended as a nursing doctoral student. The past five years have seen significant changes in symposium foci. This year, meaningful use, the amazing power of Watson, and the impending volume of patient-sourced data were major topics. In fact, during his keynote address, NIH Director Frances Collins, M.D., Ph.D., noted that the amount of data coming from patients directly will soon far outweigh clinically generated data. This year, it was very clear to me that this expanding horizon of patient-sourced data brings new opportunities for nurses and greater recognition of their role in patient care.

Seasoned nurses will remember “SOAP” charting: documentation of the subjective (S-patient reports and complaints), objective (O – clinical measurements at time of presentation) elements of the patient’s presentation, followed by a nursing assessment (A) and plan (P). Nursing informaticists have developed standard nursing terminologies and languages and demonstrated their key role in telehealth. Today’s technologies, particularly mobile health applications and their integration with a patient’s health and health care, demonstrate that there is a key role for nurses in this frontier.

Nurses know that the patient experience of health and illness that occurs outside of the clinical visit is essential to understanding the patient. In the past, documenting the patient reports, the “S”, has been limited by what our medical knowledge tries to read into a patient subjective report. The current Project HealthDesign teams’ work expands both what subjective experiences are (S) and how they can be measured (O). The inclusion of patient-sourced data into the EHR or, at minimum, clinical conversation, validates the patient’s participation in their care.

In my view, over the past five years, the AMIA symposiums have showcased an amazingly fast progression of technology and computing power. These advancements have moved from biomedical ontologies, imaging capabilities, and genomic mapping to solid advancements that have a tangible influence on the way patients can manage their own health.

November 07, 2011

Did you know clinicians can help guide federal conversations about health IT? Whether you’re a nurse, physician, health coach or other clinician, you have a unique perspective. Many clinicians are close to the patient experience and are able to translate their understandings of day-to-day health care operations into stories and statements that can impact policy-makers.

Scan for opportunities. Think about the patients and caregivers you interact with on a day-to-day basis. What types of public policy issues would impact their daily experiences? Visit regulations.gov to review policies that are currently open for public comments.

Develop partnerships.Contact your state nurses’ organization, an organization that advocates for patients with a particular care concern or a group at your clinical site. Ask these groups to help you understand what policy issues are important and timely.

Develop a message. Think about how new public policies might impact your patient population. Then state your message clearly and concisely.

Make your statement.Visit regulations.gov to leave a comment on a federal regulation, or write a letter to your state legislator to let him or her know how a proposed policy might intersect with your patient population’s needs.

November 04, 2011

For a couple of years, we have been calling our project Embedded Assessment, based on a really nice paper by Margie Morris. In that paper, Morris and colleagues defined embedded assessment as systems that serve monitoring, prevention and compensation purposes; are personalized to a user and embedded in a user’s everyday environment; and monitor health status and look for meaningful patterns that can inform health-related decision-making. Although this definition still holds for our project, we have decided to change the project name to dwellSense

There are a few reasons for the name change. First, embedded assessment describes a category of systems and not just our project. Our project is an example of an embedded assessment system. Second, the full name for our project started with “Embedded Assessment” but this is a shortened version of a longer name. Sometimes, we referred to it as “Embedded Assessment of Aging Adults.” Other times it was “Embedded assessment of wellness with smart home sensors.” Other times it was “Task-based embedded assessment of functional abilities for older adults, caregivers, and clinicians.” All of these are accurate, but none of them roll off the tongue particularly well and none is particularly memorable.

A couple of months ago, Matthew Lee, our dwellSense lead researcher, came up with the new name, dwellSense. I really like this new name. It’s short and succinct, and I think it sums up the main ideas behind our project; it includes sensors, focuses on where people live or dwell, and, as you can see by the logo, has a particular focus on wellness.

As Gillian Hayes wrote in a post about the FitBaby team changing its name to Estrellita, a name is important. Although the new name won’t make a difference to the participants in our study, it will likely impact others who hear about our project, the work we are doing, and the goals we are working toward.